Dysfunction of Foxp3+ Regulatory T Cells Induces Dysbiosis of Gut Microbiota via Aberrant Binding of Immunoglobulins to Microbes in the Intestinal Lumen
Bibliographic record
Abstract
Foxp3+ regulatory T (Treg) cells prevent excessive immune responses against dietary antigens and commensal bacteria in the intestine. Moreover, Treg cells contribute to the establishment of a symbiotic relationship between the host and gut microbes, partly through immunoglobulin A. However, the mechanism by which Treg cell dysfunction disturbs the balanced intestinal microbiota remains unclear. In this study, we used Foxp3 conditional knockout mice to conditionally ablate the Foxp3 gene in adult mice and examine the relationship between Treg cells and intestinal bacterial communities. Deletion of Foxp3 reduced the relative abundance of Clostridia, suggesting that Treg cells have a role in maintaining Treg-inducing microbes. Additionally, the knockout increased the levels of fecal immunoglobulins and immunoglobulin-coated bacteria. This increase was due to immunoglobulin leakage into the gut lumen as a result of loss of mucosal integrity, which is dependent on the gut microbiota. Our findings suggest that Treg cell dysfunction leads to gut dysbiosis via aberrant antibody binding to the intestinal microbes.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".